Magnetic resonance diffusion tensor imaging (DTI) has emerged as a convenient and reliable alternative to conventional histology for characterizing the fiber structure of the myoca...
We study a sparse coding learning algorithm that allows for a simultaneous learning of the data sparseness and the basis functions. The algorithm is derived based on a generative m...
In limited data tomography, with applications such as electron microscopy, medical imaging, industrial non-destructive testing, etc., the scanning views are within an angular rang...
In this paper, we propose a novel supervised hierarchical sparse coding model based on local image descriptors for classification tasks. The supervised dictionary training is perf...
The high dimensionality of functional magnetic resonance imaging (fMRI) data presents major challenges to fMRI pattern classification. Directly applying standard classifiers often ...
Bernard Ng, Arash Vahdat, Ghassan Hamarneh, Rafeef...